In many systems and devices, especially, for example, devices and systems which include high speed digital communication circuits, intersymbol interference and crosstalk interference between various electrical signals can be significant problems—and difficult ones to understand and diagnose.
Commonly, crosstalk interference may be produced by two signal lines coupling energy onto each other (e.g., two parallel lines radiating their signals onto each other). In general, herein, we refer to the signal which generates the crosstalk interference as an “interfering signal” or “aggressor signal,” and the signal which experiences the crosstalk interference as a “victim signal.” Of course when two signals produce mutual crosstalk interference, each signal may be both an aggressor signal in one case, and a victim signal in the other case.
Intersymbol interference (ISI), on the other hand, is caused by “aggressor bits” distorting other “victim bits” within the same serial data signal.
The ability to measure the magnitude of ISI and crosstalk for a particular serial data signal can be helpful to diagnosing and minimizing the crosstalk.
The analysis and diagnosis of crosstalk in a given device may be difficult and complicated.
For example, circuit simulation may be employed to analyze and diagnose crosstalk for one or more signal lines of a particular device. Given a circuit model of the particular device, software simulation tools may be employed to estimate the amount of crosstalk for a given signal line.
However, such circuit simulation has drawbacks. For one thing, the simulation results will only be as good as the circuit model. Producing accurate circuit models can be difficult and time-consuming as many circuits are complicated and have a large number of components. And if an accurate circuit model is produced, every time that a change is made to the device which is being analyzed, the circuit model must be updated. Furthermore, running the simulations can also require a lot of effort and can be time consuming. Moreover, it can be very difficult to produce an accurate simulation since in many cases the crosstalk may be created or affected by non-linearities and parasitic impedances in the circuit, which—unlike nominal circuit values—are typically not known in advance and may be difficult to ascertain. Because of this, crosstalk performance may vary significantly from individual device to individual device even when the devices are designed to be identical. Furthermore, in some cases (e.g., voltage-dependent power supply crosstalk) the model must be non-linear (voltage dependent) to accurately reflect the underlying crosstalk mechanisms. So, the accuracy of crosstalk estimates produced from circuit modeling and simulation is an issue.
One improvement for analyzing and diagnosing crosstalk for a device is to use actual measurements of a sample of the device to construct a circuit model, rather than constructing the circuit model from circuit diagrams or schematics. For example, to construct a circuit model for analyzing power supply crosstalk, one may disconnect the power supply from the rest of the device under test and replace it with an external supply which can be controlled to artificially generate a range of disturbance(s), and then measure the corresponding effect on the signal line(s) of interest as a function of the disturbance(s) across an expected range of interest. While this approach may potentially yield more accurate results, it can be tedious, invasive, time consuming, and require a lot of very expensive equipment.
As indicated above, in addition to crosstalk between signals (e.g., serial data signals) in a given device, power supplies can also create crosstalk interference to signals. In many cases, power supply crosstalk interference onto a victim signal can be just as important or more important to understand and diagnose as crosstalk interference between two signal lines. One reason for this is that different mechanisms and affects may pertain to power supply crosstalk as compared to crosstalk interference between two signal lines. For example, the amplitude noise that a supply voltage may add to a victim signal may be non-linear or voltage dependent. In particular, a positive supply voltage may be connected directly to the transmission line for a victim signal when the signal's level is at a “high value” (e.g., logic 1), so noise or voltage drift in the supply voltage may transfer directly to the victim signal. However the same interference may occur at a significantly reduced level when the victim signal's level is at a “low value” (e.g., logic 0). The opposite may be the case for negative supply voltages and ground, which may have more of an impact on a victim signal when the signal's level is low than when it is high.
Accordingly, the analysis and diagnosis of voltage-dependent power supply crosstalk in a given device may be particularly difficult and complicated.
It would also be desirable to provide a technique for analyzing and diagnosing ISI and crosstalk for a serial data signal of a device under test from one or more other signals. It would also be desirable to provide a technique for analyzing and diagnosing voltage-dependent power supply crosstalk in a device under test.